The present invention relates to methods for automatically generating natural-language news items from log files and status traces.
The ability to automatically generate natural-language news items could save a vast amount of resources while delivering information to concerned readers at an unprecedented response rate. Current methods known in the art typically scan existing news databases for keywords provided by a user in the user's personal preferences. However, such methods are incapable of generating news items solely from data records. Such methods can extract facts from press releases or other reported news items to harvest information for constructing new news items, but rely on the information in such published articles for providing the essence of the newsworthy attributes of the subject.
In the prior art, Mayer, in US Patent Publication No. 20050114324 (hereinafter referred to as Mayer '324), discloses a system and method for improved searching on the internet or similar networks and especially improved MetaNews and/or improved automatically generated newspapers. McFeely, in US Patent Publication No. 20020184237 (hereinafter referred to as McFeely '237), discloses methods and apparatus for compiling, processing, and disseminating equity transaction data. Zhu et al., in US Patent Publication No. 20030065502 (hereinafter referred to as Zhu '502), discloses text-based automatic content classification and grouping. However, most of these methods do not generate truly-new natural-language news items from data records. While MeFeely '237 discloses methods for analyzing such data records, the information is not developed into a typical, natural-language news story as it is commonly understood.
It would be desirable to have methods for automatically generating natural-language news items from log files and status traces. Such methods would, among other things, overcome the limitations of the prior art as described above.